The bacterial cell wall is a formidable macromolecule that circumferences the cell. In the past decade a general understanding has been gained for model organisms on the proteins, enzymes and their activities that are involved in the biosynthesis and the restructuring of the cell wall. A main conclusion derived from these studies is that the process of cell wall maintenance is extremely complex and requires the cumulative interactions of many of the involved proteins. It has been suggested that the cell wall biosynthesis machinery exists in the form of a supermolecular holoenzyme, a conclusion that is based on the results from numerous fluorescence localization studies that discovered an interdependence of subcellular localization for these enzymes. Despite these many advances much remains to be learned about the transcriptional feedback loops and posttranscriptional regulations of the involved proteins and the physiologic importance for survival. Our work on the essential WalRK signal transduction system of the Gram-positive bacteria has identified this regulatory system to connect cellular growth with the ensuing necessity for cell wall restructuring. As a consequence of these studies essential autolysin activities have been unveiled that are subject to transcriptional and posttranscriptional control and that might be targeted by the innate immune system. Building on this knowledge we propose here to discover the concerted interplay between the many players that are involved in Bacillus subtilis cell wall homeostasis as a model for Gram-positive cell wall maintenance. The identification of molecular and structural details of the protein interactions involved in cell wall restructuring is hampered y the transient nature of these interactions and by the fact that the involved proteins span all thre compartments of the cell from cytoplasm to membrane to extra-cytoplasmic space. To identify interaction parameters between interacting proteins we recently developed a computational approach. The approach relies on extensive and ever growing sequence databases, to elucidate contact residue information between interacting proteins. Recent publications and preliminary results strongly support the notion that this technology is generally applicable to decipher protein interaction information, and will now be applied to the study of important transient interaction that govern cell wall maintenance and restructuring.